Department of Mathematics and Statistics, Lancaster University, Lancaster, UK.
Stat Med. 2010 Feb 28;29(5):521-32. doi: 10.1002/sim.3822.
There is growing interest, especially for trials in stroke, in combining multiple endpoints in a single clinical evaluation of an experimental treatment. The endpoints might be repeated evaluations of the same characteristic or alternative measures of progress on different scales. Often they will be binary or ordinal, and those are the cases studied here. In this paper we take a direct approach to combining the univariate score statistics for comparing treatments with respect to each endpoint. The correlations between the score statistics are derived and used to allow a valid combined score test to be applied. A sample size formula is deduced and application in sequential designs is discussed. The method is compared with an alternative approach based on generalized estimating equations in an illustrative analysis and replicated simulations, and the advantages and disadvantages of the two approaches are discussed.
人们对在单一临床试验评估中结合多个终点指标来评估实验性治疗方法的兴趣日益浓厚，这种方法尤其适用于中风试验。终点指标可以是对同一特征的多次重复评估，也可以是不同量表上进展情况的替代衡量指标。这些终点指标通常为二分类或有序分类变量，本研究也主要针对这两种情况。本文直接对每种终点指标的单变量评分统计量进行组合，推导评分统计量之间的相关性，并利用相关性进行有效的综合评分检验。本文还推导出一个样本量公式，并讨论了序贯设计中的应用。在一个说明性分析和复制模拟中，本文将这种方法与基于广义估计方程的替代方法进行了比较，并讨论了两种方法的优缺点。
